Background

A study to assess the feasibility of applying remote sensing methodologies to evaluate riparian stand conditions on lands subject to Washington State’s forest practices regulations. The study focuses on assessing the feasibility of applying remote sensing methodologies by summarizing existing published methods and results and comparing that information against field based methods.

Our Work

Phase 1 (March - June 2015)

We are working to provide basic background information to guide the development of a Washington State riparian forests status and trends monitoring pilot project based on remote sensing methods.

Specific objectives of the project will include:

A cost assessment for all data types covered

Summary of specifications of all sensors covered in the assessment

Literature review documenting the accuracies of the methods

A break out of outcomes for direct and modeled methods

Phase 2 (November 2015 - June 2017)

We implemented a pilot project to demonstrate the effectiveness of using LIDAR and NAIP imagery to estimate various plot level forest inventory metrics.

This work included:

Developing the study design

Developing a field plot measurement guide

Field plot design, identification, and location selection

Field sampling

Development and accuracy assessment of statistical models to estimate the metrics

Preparing a summary report for the DNR

Presentation to the DNR policy board

Phase 3 (January 2018 - June 2018)

Report scoping future stages of the project with the following objectives

To identify ecosystem types that capture the majority of the diversity in Washington State, and to assess where Lidar data is available to perform future analysis as well as to assess the feasibility, assumptions and limitations of such Lidar data. Assure that the selected sites capture the range of elevation and topographic variability that drives these ecosystems and can be an issue in the Lidar models.

Identify suitable locations where temporal Lidar is available to allow for testing of the transferability of the Lidar-based models from one point in time to another point in time. Ideal location would have more than two Lidar acquisitions. Assess the feasibility, assumptions and limitations of such multi-date Lidar data.

Determine with RSAG which riparian metrics, based on their performance, should be removed from future modeling; and which metrics, based on their ecosystem function, should be included and tested in future analysis (examples: shading, forested wetlands).